AI Grinding for Fun and Cryptanalysis

📅 2026-08-22
📈 Citations: 0
Influential: 0
📄 PDF
🤖 AI Summary
研究提出一种自动密码分析工作流程,通过生成、测试和优化假设来发现密码系统的缺陷。方法包括识别代数映射错误及分布差异,已验证八个已发布构造的失败。
📝 Abstract
We present an autonomous cryptanalysis workflow in which agents generate, test, and refine hypotheses before human review. The autonomous stage returns reproducible candidates with exact witnesses, controls, code, and run records. A researcher then decides whether the evidence establishes a break, defect, or coverage gap. Two failure modes recur. First, a public algebraic map or input representation erases or exposes a relation that a construction must hide. Examples include multiplication by zero, boundary coefficients of a polynomial product, quotients, characters, Schur squares, and variable-length byte encodings without boundaries. Second, a simulator, error law, or parameter certification uses a distribution different from the one claimed. Several targets fail in both ways. Every result has an exact witness and a discriminating control; every stated boundary has a proof. Three further targets yielded no attack but support narrower guarantees than a generic reading suggests. Eight published constructions fail at stated parameters or claims. A Ring-LWR commitment opens to every message with probability one. One ciphertext reveals two middle-product encryption rows. A lattice e-voting protocol loses receipt-freeness. A permutation-recovery attack against updatable encryption extends by linear algebra to the old decryption key. An explicit normal basis splits a degree-63 instance into seven degree-nine instances. A signature hash outside the lattice setting maps two printable equal-length messages to the same digest. A rerandomisable scheme's accept bit is a threshold oracle on its decryption noise. Separately, a group-ring decision claim and a multivariate MinRank hardening fail at the assumption or accounting level rather than as complete construction breaks. Each failure occurs one level above its supporting assumption.
Problem

Research questions and friction points this paper is trying to address.

cryptanalysis
autonomous workflow
failure modes
algebraic map
distribution mismatch
Innovation

Methods, ideas, or system contributions that make the work stand out.

autonomous cryptanalysis
hypothesis generation and testing
reproducible candidates
failure modes in cryptography
exact witnesses
🔎 Similar Papers
No similar papers found.
L
Lukasz Olejnik
Department of War Studies, King’s College London; Independent Researcher
B
Bartosz Naskrecki
Faculty of Mathematics and Computer Science, Adam Mickiewicz University; Centre for Credible AI, Warsaw University of Technology